Sleep-related breathing biomarkers as a predictor of vital functions

• Autorzy: Proniewska K. , Pręgowska A. , Malinowski K. P.

Identyfikatory

DOI

10.1515/bams-2017-0003

• Języki publikacji: EN

Abstrakty

EN

Because an average human spends one third of his life asleep, it is apparent that the quality of sleep has an important impact on the overall quality of life. To properly understand the influence of sleep, it is important to know how to detect its disorders such as snoring, wheezing, or sleep apnea. The aim of this study is to investigate the predictive capability of a dual-modality analysis scheme for methods of sleep-related breathing disorders (SRBDs) using biosignals captured during sleep. Two logistic regressions constructed using backward stepwise regression to minimize the Akaike information criterion were extensively considered. To evaluate classification correctness, receiver operating characteristic (ROC) curves were used. The proposed classification methodology was validated with constructed Random Forests methodology. Breathing sounds and electrocardiograms of 15 study subjects with different degrees of SRBD were captured and analyzed. Our results show that the proposed classification model based on selected parameters for both logistic regressions determine the different types of acoustic events during sleep. The ROC curve indicates that selected parameters can distinguish normal versus abnormal events during sleep with high sensitivity and specificity. The percentage of prediction for defined SRBDs is very high. The initial assumption was that the quality of result is growing with the number of parameters included in the model. The best recognition reached is more than 89% of good predictions. Thus, sleep monitoring of breath leads to the diagnosis of vital function disorders. The proposed methodology helps find a way of snoring rehabilitation, makes decisions concerning future treatment, and has an influence on the sleep quality.

Słowa kluczowe

EN

patient monitoring; sleep-related breathing disorder; vital functions

• Wydawca: Uniwersytet Jagielloński - Collegium Medicum ; De Gruyter
• Czasopismo: Bio-Algorithms and Med-Systems
• Rocznik: 2017
• Tom: Vol. 13, no. 1
• Strony: 43--49
• Opis fizyczny: Bibliogr. 33 poz., rys.

Twórcy

autor

Proniewska K.

• Jagiellonian University Medical College, Świętej Anny 12, 31-008 Krakow, Poland

autor

Pręgowska A.

• Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5B, 02-106 Warsaw, Poland

autor

Malinowski K. P.

• Jagiellonian University Medical College, Świętej Anny 12, 31-008 Krakow, Poland

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Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)